Skip to main content
Log in

A location privacy protection scheme for convoy driving in autonomous driving era

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Convoy driving has great potential in the development of autonomous driving industry, which can bring great improvement to the utilization rate of roads and the travel experience of passengers. However, the emergence of convoy driving also brings some new challenges to the location privacy of autonomous vehicles. In this paper, a novel dynamic mixed zone establishment scheme is proposed to protect the location privacy of autonomous vehicles in convoy driving context. As the convoy is a closed group, the request for the establishment of the mix zone will be broadcast first within the convoy, followed by outside the convoy. In order to prevent pseudonym syntactic join attacks within the convoy, the proposed scheme allows autonomous vehicles to use multiple valid pseudonyms if only itself change the pseudonym in the convoy. In order to trace the real identity of the offending vehicle, the proposed scheme specifies the distribution method of the pseudonym, the legitimate vehicle can trace the real identity of the offending vehicle by submitting the pseudonym of the offending vehicle. Compared with the scheme to protect location privacy in the traditional vehicular network, the proposed scheme has less overhead and a higher level of security.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Davies A (2018) The wired guide to self-driving cars. Wired, 1–13

  2. Mohamad N M V, Ambastha P, Gautam S, Jain R, Subramaniyam H, Muthukaruppan L (2020) Dynamic Sectorization and parallel processing for device-to-device (D2D) resource allocation in 5G and B5G cellular network. Peer-to-Peer Networking and Applications, 1–9

  3. Ale L, Zhang N, Wu H, Chen D, Han T (2019) Online proactive caching in mobile edge computing using bidirectional deep recurrent neural network. IEEE Internet of Things Journal 6(3):5520–5530

    Article  Google Scholar 

  4. Zhang N, Yang P, Zhang S, Chen D, Zhuang W, Liang B, Shen X S (2017) Software defined networking enabled wireless network virtualization: Challenges and solutions. IEEE Netw 31(5):42–49

    Article  Google Scholar 

  5. Ma Y, Wang Z, Yang H (2020) Artificial intelligence applications in the development of autonomous vehicles: A survey[J]. IEEE/CAA Journal of Automatica Sinica 7(2):315–329

    Article  Google Scholar 

  6. Kebria P, Khosravi A, Salaken S (2019) Deep imitation learning for autonomous vehicles based on convolutional neural networks[J]. IEEE/CAA Journal of Automatica Sinica 7(1):82–95

    Article  Google Scholar 

  7. Gao S, Zhou M, Wang Y (2018) Dendritic neuron model with effective learning algorithms for classification, approximation, and prediction[J]. IEEE Trans Neural Netw Learning Sys 30(2):601–614

    Article  Google Scholar 

  8. Hobert L, Festag A, Llatser I, Altomare L, Visintainer F, Kovacs A (2015) Enhancements of V2X communication in support of cooperative autonomous driving. IEEE Commun Mag 53(12):64–70

    Article  Google Scholar 

  9. Calmettes T, Michel M, Damien S (2017) Driving vehicles in convoy. U.S. Patent No. 9,786,182. 10 Oct. 2017

  10. Khan MA, Boloni L (2005) Convoy driving through ad-hoc coalition formation. In: 11th IEEE real time and embedded technology and applications symposium, pp 98–105

  11. Llatser I, Jornod G, Festag A, Mansolino D, Navarro I, Martinoli A (2017) Simulation of cooperative automated driving by bidirectional coupling of vehicle and network simulators. In: 2017 IEEE Intelligent Vehicles Symposium (IV), pp 1881–1886

  12. Zhang N, Yang P, Ren J, Chen D, Yu L, Shen X S (2018) Synergy of big data and 5g wireless networks: Opportunities, approaches, and challenges. IEEE Wirel Commun 25(1):12–18

    Article  Google Scholar 

  13. Zhang N, Lu N, Cheng N, Mark J W, Shen X S (2013) Cooperative spectrum access towards secure information transfer for CRNs. IEEE J Sel Areas Commun 31(11):2453–2464

    Article  Google Scholar 

  14. Green D, Karl C, Faber F (2015) Cooperative intelligent transport systems (C-ITS) standards assessment, No. AP-R474/15

  15. Marjovi A, Vasic M, Lemaitre J, Martinoli A (2015) Distributed graph-based convoy control for networked intelligent vehicles. In: 2015 IEEE Intelligent Vehicles Symposium (IV), pp 138–143

  16. Skottke E M, Debus G, Wang L, Huestegge L (2014) Carryover effects of highly automated convoy driving on subsequent manual driving performance. Human Factors 56(7):1272–1283

    Article  Google Scholar 

  17. Li H, Pei L, Liao D, Sun G, Xu D (2019) Blockchain meets VANET: An architecture for identity and location privacy protection in VANET. Peer Peer Netw Appl 12(5):1178–1193

    Article  Google Scholar 

  18. Chen D, Zhang N, Cheng N, Zhang K, Qin Z, Shen XS (2018) Physical layer based message authentication with secure channel codes. IEEE Transactions on dependable and secure computing. https://doi.org/10.1109/TDSC.2018.2846258

  19. Hadian M, Altuwaiyan T, Liang X, Zhu H (2019) Privacy-preserving task scheduling for time-sharing services of autonomous vehicles. IEEE Trans Veh Technol 68(6):5260–5270

    Article  Google Scholar 

  20. Parkinson S, Ward P, Wilson K, Miller J (2017) Cyber threats facing autonomous and connected vehicles: Future challenges. IEEE Trans Intell Transpo Syst 18(11):2898–2915

    Article  Google Scholar 

  21. Zhou L, Yu L, Du S, Zhu H, Chen C (2018) Achieving differentially private location privacy in edge-assistant connected vehicles. IEEE Internet of Things Journal 6(3):4472–4481

    Article  Google Scholar 

  22. Deng E, Zhang H, Wu P, Guo F, Liu Z, Zhu H, Cao Z (2019) Pri-RTB: Privacy-preserving real-time bidding for securing mobile advertisement in ubiquitous computing. Information Sciences 504:354–371

    Article  Google Scholar 

  23. Ardagna C, Cremonini M, Damiani E (2007) Location privacy protection through obfuscation-based techniques[C]. In: IFIP Annual conference on data and applications security and privacy. Springer, Heidelberg, pp 47–60

  24. Xu T, Cai Y (2009) Feeling-based location privacy protection for location-based services[C]. Proceedings of the 16th ACM conference on computer and communications security, pp 348–357

  25. Miyazawa M, Tanabe H, Yamane M, Sen N, Yashima J, Nakahama H, Ishiyama M, Hiroma T (2019) Convoy travel control apparatus. U.S. Patent 10,262,541[P]. 2019-4-16

  26. Chen D, Zhang N, Lu R, Cheng N, Zhang K, Qin Z (2018) Channel precoding based message authentication in wireless networks: Challenges and solutions. IEEE Netw 33(1):99–105

    Article  Google Scholar 

  27. Chen D, Zhang N, Lu R, Fang X, Zhang K, Qin Z, Shen X (2018) An LDPC code based physical layer message authentication scheme with prefect security. IEEE J Sel Areas Commun 36(4):748–761

    Article  Google Scholar 

  28. Mo R, Ma J, Liu X, Liu H (2018) EOABS: Expressive outsourced attribute-based signature. Peer Peer Netw Appl 11(5):979–988

    Article  Google Scholar 

  29. Adavoudi-Jolfaei A, Ashouri-Talouki M, Aghili S F (2019) Lightweight and anonymous three-factor authentication and access control scheme for real-time applications in wireless sensor networks. Peer Peer Netw Appl 12(1):43–59

    Article  Google Scholar 

  30. Chen D, Zhang N, Qin Z, Mao X, Qin Z, Shen X, Li X Y (2016) S2M: A lightweight acoustic fingerprints-based wireless device authentication protocol. IEEE Internet of Things Journal 4(1):88–100

    Article  Google Scholar 

  31. Teramoto T, Matsuura S, Kakiuchi M, Inomata A, Fujikawa K (2013) Location tracking prevention with dummy messages for vehicular communications. In: 2013 13th International Conference on ITS Telecommunications (ITST), pp 56–61

  32. Pan X, Xu J, Meng X (2011) Protecting location privacy against location-dependent attacks in mobile services. IEEE Trans Knowl Data Eng 24(8):1506–1519

    Article  Google Scholar 

  33. Palanisamy B, Liu L (2011) Mobimix: Protecting location privacy with mix-zones over road networks. In: 2011 IEEE 27th International conference on data engineering, pp 494–505

  34. Huang L, Matsuura K, Yamane H, Sezaki K (2005) Enhancing wireless location privacy using silent period. In: IEEE Wireless Communications and Networking Conference, vol 2, pp 1187–1192

  35. Buttyn L, Holczer T, Weimerskirch A, Whyte W (2009) Slow: A practical pseudonym changing scheme for location privacy in vanets. In: 2009 IEEE Vehicular Networking Conference (VNC), pp 1–8

  36. Song J-H, Wong VWS, Leung VCM (2010) Wireless location privacy protection in vehicular ad-hoc networks. Mob Netw Appl 15(1):160–171

    Article  Google Scholar 

  37. Ying B, Makrakis D, Hou Z (2015) Motivation for protecting selfish vehicles’ location privacy in vehicular networks. IEEE Trans Veh Technol 64(12):5631–5641

    Article  Google Scholar 

  38. Sampigethaya K, Huang L, Li M, Poovendran R, Matsuura K, Sezaki K (2005) CARAVAN: Providing location privacy for VANET. Washington Univ Seattle Dept of Electrical Engineering

  39. Kang J, Yu R, Huang X (2016) Location privacy attacks and defenses in cloud-enabled internet of vehicles[J]. IEEE Wirel Commun 23(5):52–59

    Article  Google Scholar 

  40. Petit J, Schaub F, Feiri M (2017) Pseudonym schemes in vehicular networks: A survey[J]. IEEE Commun Surv Tutor 17(1):228–255

    Article  Google Scholar 

  41. Tsang P P, Kapadia A, Cornelius C, Smith S W (2009) Nymble: Blocking misbehaving users in anonymizing networks. IEEE Trans Dependable Secure Comput 8(2):256–269

    Article  Google Scholar 

  42. Heron S (2009) Advanced encryption standard (AES). Netw Secur 12:8–12

    Article  Google Scholar 

  43. He D, Zeadally S, Xu B (2015) An efficient identity-based conditional privacy-preserving authentication scheme for vehicular ad hoc networks[J]. IEEE Trans Info Forensics Sec 10(12):2681–2691

    Article  Google Scholar 

  44. Bai L, Zhang Y, Yang G (2012) SM2 cryptographic algorithm based on discrete logarithm problem and prospect[C]. In: 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, pp 1294–1297

  45. Du S, Zhu H, Li X, Ota K, Dong M (2013) Mixzone in motion: Achieving dynamically cooperative location privacy protection in delay-tolerant networks. EEE Trans Veh Technol 62(9):4565–4575

    Article  Google Scholar 

  46. Brinkhoff T, Thomas B (2012) Network-based generator of moving objects. Available:http://iapg.jade-hs.de/personen/brinkhoff/generator. Accessed 12 July 2012

  47. Pigatto D, da Silva N, Branco K (2011) Performance evaluation and comparison of algorithms for elliptic curve cryptography with El-Gamal based on MIRACL and RELIC libraries[J]. J Appl Comput Res 1 (2):95–103

    Google Scholar 

Download references

Acknowledgments

This work is jointly supported by NSFC (No. 61872059 and 61502085), and the project “The Verification Platform of Multi-tier Coverage Communication Network for oceans” (No.LZC0020).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhiguang Qin.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article belongs to the Topical Collection: Special Issue on Privacy-Preserving Computing

Guest Editors: Kaiping Xue, Zhe Liu, Haojin Zhu, Miao Pan and David S.L. Wei

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ye, X., Zhou, J., Li, Y. et al. A location privacy protection scheme for convoy driving in autonomous driving era. Peer-to-Peer Netw. Appl. 14, 1388–1400 (2021). https://doi.org/10.1007/s12083-020-01034-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-020-01034-w

Keywords

Navigation